Relational databases are often used to collect and manage large amounts of data. For data that is collected often, where the data in the database grows quickly, such as stock market data, utility meters (i.e., collecting utility usage by customers), etc., time series databases may provide a better solution. In a relational database, a new row is added as data is collected. In a time series data, an array in a row grows larger as data is collected instead of adding a new row. However, extracting and analyzing time series data using a data warehouse is difficult since not all database tools can manage time series data.